Ilaria Mileti

TL;DR: This narrative review aims to address the topic of balance and wireless sensors in several neurological disorders, including Alzheimer's disease, Parkinson’s disease, multiple sclerosis, stroke, and other neurodegenerative and acute clinical syndromes.

TL;DR: A solution for the recognition of postural patterns through wearable sensors and machine-learning algorithms fed with kinematic data is proposed for reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders.

TL;DR: The results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors through a novel synthetic index called Gait Phase Quality Index (GPQI), which resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score.

TL;DR: The performance of a low-cost markerless system, consisting of the open-source library OpenPose, two webcams and a linear triangulation algorithm, was characterized and validated in terms of 3D kinematic gait analysis, by comparison with inertial sensors.

TL;DR: Comparing the results of the patients with the ones gathered from the control group, the WAKE-up ankle-module demonstrates that it is potentially useful for the rehabilitation of gait patterns, avoiding pathological events caused by equinus foot.